Additional Tennessee Eastman Process Simulation Data for Anomaly Detection 核心 · 已核验

atlas:tennessee-eastman-process-rieth

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<h3> Description </h3>

<p>This dataverse contains the data referenced in Rieth et al. (2017). Issues and Advances in Anomaly Detection Evaluation for Joint Human-Automated Systems. To be presented at Applied Human Factors and Ergonomics 2017.

<p>Each .RData file is an external representation of an R dataframe that can be read into an R environment with the 'load' function. The variables loaded are named ‘fault_free_training’, ‘fault_free_testing’, ‘faulty_testing’, and ‘faulty_training’, corres

落地页

https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/6C3JR1

许可证

Custom terms specific to this dataset (判读置信:inferred)

国内可访问性

国内直连:可达 (2026-07-11 检测) 代理通道:可达 (2026-07-11 检测)
检测口径:lychee 双通道单轮探测;「直连超时」表示检测窗口内未完成,系慢或不稳定证据,不构成封锁证据。

发布年份

2017

发布方

Harvard Dataverse

设备类型

industrial_process

PHM 任务

fault_detection anomaly_detection

故障工况

传感器

运行工况